Different mutation operators have been developed in evolutionary programming. However, each operator may only be efficient in certain specific fitness landscapes only. In order to combine the advantages of different operators, the mixed strategy has been proposed and achieved some success. Currently, the design of mixed strategy is mainly based on the performance of applying each operator (i.e. a strategy which produce a higher fitness will receive a better reward), but little is relevant directly to the information of local fitness landscape. In this paper a new mixed strategy is proposed which adapts to local fitness landscape. A measure is given to describe the feature of local fitness landscape. Based on this measure, a mixed strategy is designed for adapting local fitness landscape. Experiment of results on several tests show that the algorithm is efficient.

en

dc.format.extent

6

en

dc.language.iso

eng

dc.relation.ispartof

en

dc.title

Evolutionary Programming Using a Mixed Strategy Adapting to Local Fitness Landscape

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dc.type

Text

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dc.type.publicationtype

Conference paper

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dc.contributor.institution

Aberystwyth University

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dc.description.status

Non peer reviewed

en

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